Title :
Solar power probabilistic forecasting by using multiple linear regression analysis
Author :
Abuella, Mohamed ; Chowdhury, Badrul
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of North Carolina at Charlotte, Charlotte, NC, USA
Abstract :
Variable energy generation, particularly from renewable energy resources such as wind and solar energy plants have created operational challenges for the electric power grid because of the uncertainty involved in their output in the short term. Energy forecasting can be used to mitigate some of the challenges that arise from the uncertainty in the resource. While wind energy forecasting has already undergone extensive research efforts, solar power forecasting is only recently witnessing an increased amount of attention. This paper proposes a multiple linear regression analysis model to generate probabilistic forecasts of solar energy.
Keywords :
load forecasting; regression analysis; solar power stations; energy forecasting; multiple linear regression analysis; solar power probabilistic forecasting; Analytical models; Buildings; Correlation; Forecasting; Predictive models; Probabilistic logic; Wind forecasting; Probabilistic forecasting; multiple linear regression; solar energy forecasts;
Conference_Titel :
SoutheastCon 2015
Conference_Location :
Fort Lauderdale, FL
DOI :
10.1109/SECON.2015.7132869